Managing a chronic disease or ongoing health condition requires the monitoring and controlling of a physical or mental parameter of the health condition. Examples of these parameters include blood glucose in diabetes, respiratory flow in asthma, blood pressure in hypertension, cholesterol in cardiovascular disease, weight in eating disorders, T-cell or viral count in HIV, and frequency or timing of episodes in mental health disorders. Because of the continuous nature of these health conditions, their corresponding parameters must be monitored and controlled on a regular basis by the patients themselves outside of a medical clinic.
Typically, the patients monitor and control these parameters in clinician assisted self-care or outpatient treatment programs. While these outpatient treatment programs offer significant advantages for patients and healthcare providers, they present the assisting clinician with two problems in effectively managing the medical priorities of his or her patients.
The first problem is in determining each patient's current medical status. Since the patients themselves monitor their health conditions, the clinician is often limited to learning each patient's status strictly through patient initiated events, such as an emergency visit or the delivery of the patient's latest medical data. Even with the current availability of remote monitoring devices that store and transmit medical data from a patient's home to a clinic, the clinician must still wait for medical information whose arrival depends on the patient's initiative.
As a result, the majority of the clinician's time is spent with the patients who are the most motivated and eager for a response, while the greatest medical needs remain with the unmotivated patients who do not visit the clinician or transmit their medical data. These unmotivated patients often develop urgent medical needs that could have been prevented with proper medical management. Consequently, the cost of treating their chronic health conditions is much higher than one might expect given the sophistication of current medical monitoring devices.
The second problem is in determining which patients are having the greatest difficulty in controlling their health condition so that the clinician may focus attention on these patients. Unfortunately, most existing healthcare information systems are only designed to display medical data on an individual patient basis. Few systems have been developed that enable clinician's to view medical data for an entire group of patients simultaneously. Consequently, it is extremely difficult for a clinician to prioritize his or her time and efforts in a manner that optimizes care and minimizes costs and complications for the entire group of patients.
Many systems have been developed for remote monitoring of a group of patients. For example , U.S. Pat. No. 5,357,427 issued to Langen et al. on Oct. 18, 1994 describes a system for simultaneous remote monitoring of a group of high risk patients using artificial intelligence. The system includes for each patient a remote monitoring device, such as a blood pressure cuff, glucometer, etc. The remote monitoring device is connected to a telemedical interface box which transmits monitored data over a telephone line to a data recording system. Data is also collected from each patient using an artificial intelligence program that asks the patient questions through a telephone. A computer is connected to the recording system to display individual patient messages indicating a current symptom of one of the patients.
Although Langen's system does allow simultaneous monitoring of a group of patient's, it lacks a display mechanism for simultaneously displaying summary data for the entire group of patients. Langen's system also lacks a mechanism for indicating which patients have been out of contact with the clinician and therefore have an unknown current medical status. Consequently, Langen's system is ineffective in aiding the clinician to prioritize his or her time and efforts in managing the medical priorities of an entire group of patients.
Another medical monitoring system designed to monitor a group of patients is disclosed in U.S. Pat. No. 5,331,549 issued to Crawford on Jul. 19, 1994. Crawford's system includes a plurality of vital signs monitors for monitoring a plurality of patients, each monitor providing continuous data to a central server. A supervisory screen is connected to the server to display a normal status or varying levels of alarm status of the vital signs of individual patients. The system permits an overview display of a hospital floor as well as a zoom in display of an individual patient site. The system further provides a warning alarm signal when any one or more vital signs of an individual patient is outside of a predetermined limit.
While Crawford's system does allow simultaneous viewing of the vital sign status of each patient in a group, it is only directed at monitoring a group of patients who are continually connected to their vital sign monitors. Crawford's overview screen lacks any mechanism for indicating which patients have been out of contact with a clinician since continual contact is assumed.
Further, the summary data presented for each patient on the overview screen is limited to an indication of a normal state or alarm state of each patient's vital signs. Consequently, the system only allows a clinician to determine which patients are having the greatest difficulty in controlling their health condition when an actual emergency situation exists. Thus, Crawford's system is effective as a medical alarm system, but of little use to a clinician in managing the medical priorities of a group of patients who are not continually monitored in a healthcare facility.